DEA-C01 Data Ingestion and Transformation Practice Question
A company ingests streaming data from social media feeds into Amazon Kinesis Data Streams. The data is consumed by an AWS Lambda function that transforms and writes to Amazon S3. Recently, the Lambda function started timing out and dropping records. The data volume has tripled. Which actions should the data engineer take to resolve this? (Choose TWO.)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the number of shards in the Kinesis data stream
(increase shards) increases the Kinesis stream's throughput capacity to handle the tripled data volume, reducing backpressure on the Lambda consumer. Option E (increase Lambda memory) also increases CPU allocation, allowing the Lambda function to process each record faster, which helps prevent timeouts. Option B (replace Lambda with Firehose) could be an alternative but is not a direct fix for the existing Lambda-based architecture and may not be suitable for complex transformations. Option C (increase timeout to 15 minutes) might allow more time but does not address the underlying root cause of insufficient throughput or processing power. Option D (reserved concurrency) prevents other functions from affecting this function's concurrency but does not increase total processing capacity; it could even limit scaling if set too low.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Increase the number of shards in the Kinesis data stream
Why this is correct
More shards increase throughput capacity.
- ✗
Replace Lambda with Amazon Kinesis Data Firehose for the transformation
Why it's wrong here
Firehose does not support custom transformations natively; would require Lambda pre-processing.
- ✗
Increase the Lambda function timeout to 15 minutes
Why it's wrong here
Timeout alone doesn't solve processing bottleneck.
- ✗
Set a reserved concurrency on the Lambda function
Why it's wrong here
Limits concurrency, could worsen the problem.
- ✓
Increase the memory allocated to the Lambda function
Why this is correct
More memory provides more CPU, reducing processing time.
Visual reference
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.